A hierarchically sampling global sparse transformer in data stream mining for lightweight image restoration

A hierarchically sampling global sparse transformer in data stream mining for lightweight image restoration

With the rapid development of information technology, mining valuable information from multi-source data stream is essential for redundant data, particularly in image processing; the image is degraded when the image sensor acquires information. Recently, transformer has been applied to the image res...

Full description

Bibliographic Details
Main Authors: Kong, S. (Author), Liu, S. (Author), Shi, M. (Author), Tan, M. (Author), Wang, C. (Author), Zao, B. (Author)
Format: Article
Language:English
Published: Springer Science and Business Media Deutschland GmbH 2023
Subjects:
Complex networks
Computational complexity
Data stream
Data streams mining
Global sparse attention
Image enhancement
Image reconstruction
Image restoration
Image texture
Images processing
Multisource data
Performance
Redundant data
Restoration
Spatial resolution
Stochastic sampler
Stochastic systems
Textures
Transformer
Online Access:View Fulltext in Publisher
View in Scopus

Internet

View Fulltext in Publisher
View in Scopus

Similar Items